E-VaaS: Edge-Enabled Vehicle-as-a-Service for Smart Transportation Systems

Abstract

Traffic congestion and low vehicle occupancy rates pose significant challenges in urban areas, highlighting the need for efficient, shared transportation systems. Hence, in this work, we introduce an Edge-Enabled Vehicle-as-a-Service scheme, named E-VaaS, designed to improve traffic flow, reduce travel times, and enhance user satisfaction in intelligent transportation networks. By combining the Gale-Shapley stable matching algorithm with edge computing, the proposed E-VaaS system effectively schedules and matches riders to vehicles based on metrics that include travel time, distance, and cost. With the help of edge computing, E-VaaS enables low-latency processing, ensuring that ride-matching decisions are made swiftly and improving system responsiveness and user experience. Experimental results validate the effectiveness of the model, showing improved vehicle occupancy, reduced travel times and costs, and a balanced distribution of shared vehicles across the transportation network. This research advances the development of stable, scalable, and efficient ride-sharing solutions for urban environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.